RDP 2014-13: Mortgage-related Financial Difficulties: Evidence from Australian Micro-level Data 1. Introduction
November 2014 – ISSN 1320-7229 (Print), ISSN 1448-5109 (Online)
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Housing loans account for a large proportion of both households' and lenders' balance sheets. The incidence of mortgage-related financial difficulties is, therefore, an important indicator of the financial health of households and lenders.
The pronounced deterioration of housing loan performance in the United States in the mid to late 2000s, and its role in contributing to the global financial crisis, has stimulated research into the determinants of mortgage default in the United States. In contrast, there appears to be little publicly available research on this topic in Australia.[1] This may be because the economic downturn in Australia was relatively mild and the associated deterioration in housing loan performance was, by international standards, benign (Figure 1). There has also been a paucity of adequate data; only a relatively short span of aggregate data on loan performance and some key explanatory variables, such as lending standards, has been available. These factors have made it difficult to examine the determinants of mortgage-related financial difficulties in Australia using aggregate data on housing loan performance. Instead, micro-level data are needed.
In this paper, we investigate the factors associated with mortgage-related financial difficulties in Australia using two separate, but complementary, micro-level datasets: loan-level securitised mortgage data from two Australian banks and household-level data from the HILDA Survey. The datasets are complementary for two reasons:
- They include different types of information on loan, borrower and collateral characteristics. For instance, the loan-level dataset contains detailed information on loan characteristics, such as the LVR at origination and the actual interest rate charged on the loan, while the household-level dataset provides rich information on borrower characteristics, such as income and labour force status.
- They provide different perspectives on mortgage-related financial difficulties. The loan-level data provide information on how many days a loan is in arrears (i.e. behind schedule on its required payments). This allows us to analyse the factors associated with 90+ day arrears, which are a precursor to default and possible loan losses for lenders. In contrast, the household-level data identify whether a household has missed at least one mortgage payment in the past year. While less severe than falling into 90+ day arrears, this measure provides insight into the early stages of mortgage-related financial difficulties.
The literature on mortgage-related financial difficulties typically focuses on two broad theories of mortgage default. Under both theories, households default in order to best smooth consumption in the face of unexpected shocks to their housing wealth, income or required expenditure. While this paper does not attempt to formally test the two theories, they provide a useful framework for considering the factors that drive mortgage-related financial difficulties.
So-called ‘equity’ theories of default assume that the decision to default is based on a rational comparison of the financial costs and benefits of continuing to make mortgage payments. Under these theories, default is analogous to a borrower exercising a put option when the value of their mortgaged property falls sufficiently relative to their outstanding mortgage debt (i.e. when the option is ‘in the money’). These theories therefore emphasise the role of dwelling prices and amortisation (the extent of principal repayment) in explaining mortgage default. However, empirical studies commonly find that borrowers do not default as soon as they enter negative equity (e.g. Fuster and Willen 2013; Gerardi et al 2013). This may be due to the costs associated with default, including reputational costs and the associated negative effects on future access to credit (Elul 2006).
In contrast, ‘ability-to-pay’ theories maintain that borrowers do not strategically default based on their equity position, but only default when their incomes no longer cover their minimum loan payments and some subsistence level of expenditure. These theories focus on the role of liquidity constraints and credit market imperfections in explaining mortgage default.
These two theories are sometimes combined into so-called ‘double-trigger’ theories of default. Under these theories, borrowers only default if they experience a shock that makes them unable to pay their mortgage and they have negative housing equity.[2] An ability-to-pay shock, such as a negative shock to income, should not be sufficient on its own for a borrower to default. This is because a borrower with positive housing equity can sell the mortgaged property to pay back the loan or reduce their payment size by refinancing. However, these options are not typically available when the borrower has negative equity. Furthermore, negative equity should not be sufficient for a borrower to default; if the borrower expects housing prices to recover and default is not costless, it may be optimal for the borrower to continue to service the loan. Additionally, borrowers may delay default if they expect further significant dwelling price falls, as the value of the default option increases with falling dwelling prices (Kau, Keenan and Kim 1994).
Empirical approaches to testing theories of mortgage default have been eclectic, with studies simultaneously investigating both equity and ability-to-pay factors using a variety of models and data (e.g. aggregate data, loan-level data and household-level surveys). These studies generally find that ability-to-pay and equity factors are both important in determining whether a borrower defaults. Some US studies find evidence of strategic default (e.g. Ghent and Kudlyak 2010), although the level of negative equity at which this occurs has been estimated to be quite high (Bhutta, Dokko and Shan 2010). Some studies find that ability-to-pay factors, such as unemployment and the mortgage interest rate, play a large role in mortgage default behaviour (e.g. Fuster and Willen 2013). Other studies find that both factors, and sometimes their interaction, are important (e.g. Elul et al 2010; Gerardi et al 2013). Appendix A summarises some recent international studies of mortgage default.
Our paper makes two key contributions to the literature on mortgage-related financial difficulties. First, to the best of our knowledge, this is the first paper to use micro-level data to quantitatively analyse mortgage-related financial difficulties in Australia. Second, we find evidence to suggest that both ability-to-pay and equity factors have significant correlations with the incidence of mortgage-related financial difficulties.
This paper provides a useful input into the analysis of housing finance in Australia for a few reasons. First, the micro-level analysis provides a new ‘bottom-up’ assessment of the risks associated with housing lending. Second, the information could be used as an input into stress tests of the housing lending exposures of authorised deposit-taking institutions and mortgage insurers. Third, it could be useful in informing decisions about the design of the prudential policy framework. More broadly, the information could help to inform decisions about the level of risk that lenders, their investors and regulators are willing to accept.
The remainder of the paper is organised as follows. In Section 2, we analyse entry into 90+ day housing loan arrears using newly available loan-level data and a competing risks regression framework. In Section 3, we analyse missed mortgage payments using the HILDA Survey and a discrete choice modelling framework. Finally, Section 4 concludes.